(PS8-67) Enhancing Digital Phenotyping Implementation in Digital Psychiatry: The Role of Visualizations in Advancing Treatment for Anxiety and Depression

Digital phenotyping is increasingly utilized in psychiatric clinics, particularly in digital interventions, to improve treatment outcomes. However, a critical gap remains in how this data is shared, interpreted, and integrated into clinical workflows. While previous efforts have focused on visualizing statistical data, many approaches lack accessibility, flexibility, and adaptability for diverse clinical needs. To address these challenges, we developed a structured visualization framework that translates raw digital phenotyping data into meaningful insights, enhancing communication between clinicians, digital navigators, and patients.

This project outlines our process for transforming raw digital phenotyping data into intuitive visual representations that enhance clinical interpretation and intervention outcomes within eight-week, short-term digital evidence-based treatments for patients with primary anxiety and depression disorders. We detail the structure and functionality of these visual outputs, emphasizing their role in weekly clinical sessions to support informed decision-making. Additionally, we present feedback from clinicians (N=22) on the usability and practicality of these visualizations across various clinical and research settings.

Findings suggest that these enhanced visualizations significantly improve clinicians’ ability to interpret digital phenotyping data, facilitating more effective patient communication and treatment adjustments. Clinicians reported increased efficiency in tracking symptom changes, identifying patterns, and engaging patients in discussions about their progress. Furthermore, different research groups demonstrated varying adaptation strategies, highlighting the need for implementation flexibility across clinical settings.

This work underscores the potential of digital phenotyping visualizations to bridge the gap between data collection and clinical application, ultimately enhancing intervention effectiveness. By integrating these tools into standard psychiatric care, we can improve data accessibility, support personalized treatment planning, and optimize the overall efficiency of digital mental health interventions.